/01
Monitoring layer
Implement and harden provider integrations and scraping workflows for the agreed AI answer engines.
/01 · Executive summary
Expand the platform without losing operational control.
The mandate
Expand and scale Llumo's enterprise-grade AI search visibility tracking platform.
Monitoring
Support ChatGPT, Google AI Overviews, Perplexity, Gemini, Copilot, and Grok.
Data foundation
Strengthen API integrations, web scraping, and aggregation pipelines for AI answer data.
$100K USD
Budgetary fixed investment. Final scope, schedule, and payment milestones will be confirmed in the statement of work.
/02 · Requirements
What the platform must cover.
- Monitor answers across ChatGPT, Google AI Overviews, Perplexity, Gemini, Copilot, and Grok.
- Track brand mentions, citations, competitor visibility, and source attribution.
- Collect data through robust API integrations and scalable web scraping.
- Normalize and aggregate answer-engine data for consistent analysis.
- Report visibility, share of voice, citations, sources, competitors, and trends through dashboards.
Source: the supplied Llumo opportunity brief and llumohq.com.
/03 · Proposed approach
Connect. Normalize. Report.
/02
Data pipeline
Capture, normalize, aggregate, and store answers, citations, sources, brand mentions, and competitor references.
/03
Reporting layer
Extend dashboards for visibility, share of voice, citations, source attribution, competitors, and trend analysis.
/04 · Scope and deliverables
Milestones tied to reviewable outputs.
| Milestone | Deliverable | Accepted when |
|---|---|---|
| M1 · Discovery | Current-state review, target architecture, and prioritized delivery backlog | Llumo approves the architecture, delivery priorities, and acceptance plan |
| M2 · Monitoring | Agreed AI answer engine integrations and execution workflows | The agreed test prompts run through the selected engines and produce reviewable response records |
| M3 · Data | Scraping, normalization, aggregation, and storage pipeline | Records expose the agreed answer, citation, source, brand, and competitor fields |
| M4 · Reporting | Dashboard reporting for visibility, citations, source attribution, competitors, and trends | Llumo can review the agreed reporting dimensions and filters in staging |
| M5 · Release | Production release, operational documentation, and handover | The agreed production checklist is complete and documentation is delivered |
/05 · Delivery sequence
Start with the architecture, then scale the platform.
Target start from the supplied brief: August 29, 2026. Phase duration and calendar dates will be confirmed after discovery.
Phase 1
Discovery and architecture
Confirm the current platform, target engines, data model, operational constraints, and acceptance plan.
Phase 2
Monitoring and collection
Implement and harden the agreed integrations and web-scraping workflows.
Phase 3
Aggregation and reporting
Normalize collected data and extend dashboard reporting across the agreed visibility dimensions.
Phase 4
Release and handover
Complete production readiness, operational documentation, and handover.
/06 · Investment
One focused engagement.
A budgetary fixed investment aligned with the requested approximately $100K scope.
Recommended
Platform expansion
$100K USD
AI answer engine monitoring, scalable data collection, aggregation, dashboard reporting, and production release.
- Discovery and target architecture
- Monitoring integrations
- Scraping and data pipelines
- Dashboard reporting
- Release documentation and handover
/07 · Assumptions and boundaries
Confirm before the statement of work.
Assumptions
- Llumo provides access to the current codebase, environments, data model, and relevant provider credentials.
- The target engines, prompt volumes, refresh cadence, retention rules, and dashboard roles are confirmed during discovery.
- Llumo provides one product decision-maker for scope and milestone review.
Not included in this budgetary proposal
- Third-party AI provider, proxy, scraping, hosting, and infrastructure usage fees.
- Managed AEO services or content production.
- Native mobile applications.
- Features not included in the approved delivery backlog.
Confirm scope. Finalize the statement of work.
Review the current platform, priorities, target engines, and delivery constraints